Label-free, low-cost AI ranking for systematic review screening

Title and abstract screening is among the most labor-intensive steps of systematic reviews. Jev, a low-cost AI decision model, scores records against eligibility criteria without screening labels. We scored 169,982 records from 128 reviews and, after tuning on development reviews, evaluated 23 held-out reviews once and 31 Cochrane reviews post hoc. Jev outranked the best free ranker in all 23 held-out reviews (mean AUC 0.966 vs 0.831) and came within 0.011 AUC of Claude Opus 5.5 on 1999 records at about 1/700 of its list-price cost (US$0.02/1000 records). Combined with active learning, it rais

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